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Cluster-Based Energy-Efficient Communication in Underwater Wireless Sensor Networks Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Air Pollution Prediction Using Extreme Learning Machine: A Case Study on Delhi (India)

Authors : Manisha Bisht, K. R. Seeja

Published in: Proceedings of First International Conference on Smart System, Innovations and Computing

Publisher: Springer Singapore

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Abstract

Outdoor air pollution has emerged as a serious threat to public health across the globe. Air quality monitoring and forecasting are required to provide the policy makers a scientific basis for formulating a robust policy on abatement of air pollution. Moreover, if air pollution forecasts are issued to the public, they can take preventive measures to minimize their exposure to unsafe levels of air pollutants. In this paper, an intelligent air pollution prediction system using Extreme Learning Machine (ELM) has been proposed to predict the air quality index for five pollutants (PM10, PM2.5, NO2, CO, O3) for the next day. It is found that the prediction of ELM-based proposed system is better than the existing air pollution prediction systems.

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Metadata
Title
Air Pollution Prediction Using Extreme Learning Machine: A Case Study on Delhi (India)
Authors
Manisha Bisht
K. R. Seeja
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of First International Conference on Smart System, Innovations and Computing

Print ISBN: 978-981-10-5827-1

Electronic ISBN: 978-981-10-5828-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-5828-8_18

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